cd E:\karthi_m\wind
E:\karthi_m\wind
import pandas_profiling
import pandas as pd
da=pd.read_csv('data1.csv')
da.columns
Index(['power', 'windspeed', 'airdensity', 'amb_temp', 'nac_direction',
'blds_pitchangle', 'rtr_rpm', 'gen_rpm', 'wtg_state'],
dtype='object')
da['wtg_state'].value_counts()
ok 44020 wind low 8658 curtailed 4187 Gen not conn 3896 high wind cut-out 29 Name: wtg_state, dtype: int64
da.head()
| power | windspeed | airdensity | amb_temp | nac_direction | blds_pitchangle | rtr_rpm | gen_rpm | wtg_state | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | 964.5 | 9.1 | 1.162127 | 27 | 61.8 | -3.0 | 14.1 | 1305.0 | ok |
| 1 | 1025.1 | 9.6 | 1.162127 | 27 | 61.8 | -3.1 | 14.4 | 1336.0 | ok |
| 2 | 1179.7 | 9.6 | 1.162127 | 27 | 61.8 | -2.9 | 14.4 | 1330.0 | ok |
| 3 | 1754.5 | 11.2 | 1.162127 | 27 | 65.2 | -1.5 | 14.5 | 1345.0 | ok |
| 4 | 1826.8 | 11.4 | 1.162127 | 27 | 66.6 | -1.3 | 14.5 | 1344.0 | ok |
pandas_profiling.ProfileReport(da)
profile = pandas_profiling.ProfileReport(da)
rejected_variables = profile.get_rejected_variables()
rejected_variables
profile = pandas_profiling.ProfileReport(iris_data)
profile.to_file(outputfile="../profiling_iris.html")